4 ms·

Detecting black faces correctly is one thing; obviously if a system can't do that it's an issue and it shows that the people making the system were biased. But

Detecting black faces correctly is one thing; obviously if a system can't do that it's an issue and it shows that the people making the system were biased. But something like Copilot or DALL-E? If you ask DALL-E for a doctor and it rarely shows black people (or women), then it is neither racist nor broken. Our society is broken. There are not enough people in that job that are not white and male. Or they are not represented enough. I think there is value in AI that honestly reflects society, because it makes this discrepancy harder to ignore. People imagined AI would be this benevolent, neutral, wise thing that would maybe be a bit naive but not have our human biases. But it turns out there is no "morally neutral". It will just reflect what you put into it.

mlyle 4y ago
> There are not enough people in that job that are not white and male. Have you looked at the actual demographics of medical doctors in the US? 54% are women, and 35% are nonwhite. But when we have media depictions of doctors, I agree they tend to be white and male. So, what should DALL-E conform to? Should it conform to A) our actual present society, B) the biased original dataset (which leans both towards the past and towards existing media biases), or C) some idealized version of society? I got 12 white dudes, one Southeast Asian woman, one Southeast Asian looking man, and two men that I'm not sure of their race when I tried this just now (quite possibly white). This is despite OpenAI's efforts to debias it, and isn't representative of current physician demographics. But if AI just represents and reinforces extant biases-- and worse, AI is used to produce art and text that ends up in other AIs training sets -- how do we ever get out of this mess? The people who produce, publish, and productize AI do have some degree of editorial responsibility. > But it turns out there is no "morally neutral". Of course not. Hume pointed out long ago that you can't transform positive statements into normative ones. But all of this is a little offtopic, anyways. This is about when it's reasonable to refuse to return a result. "Hey, your answer had the N-word in it, and we know most of the time our model does that it's offensive-- so we're just not going to return a result, sorry." I think this is a reasonable path to take when you know that your model has some behaviors that are socially questionable.
- GameOfFrowns 4y ago
  >54% are women, and 35% are nonwhite. But when we have media depictions of doctors, I agree they tend to be white and male What's the issue? I used to watch a lot of medical dramas on TV and in my opinion the black rockstar MDs are way overrepresented in comparison to their real-life numbers: '5.0%' in 2018 in the US[1] in real-life vs. '19.4%'[2] on TV [1]https://www.aamc.org/data-reports/workforce/interactive-data/figure-18-percentage-all-active-physicians-race/ethnicity-2018 https://www.aamc.org/data-reports/workforce/interactive-data... [2]https://www.bluetoad.com/publication/?i=671309&article_id=3748569&view=articleBrowser&ver=html5 https://www.bluetoad.com/publication/?i=671309&article_id=37...
  - mlyle 4y ago
    > What's the issue? I used to watch a lot of medical dramas on TV and in my opinion the black rockstar MDs are way overrepresented in comparison to their real-life numbers: Well, this clearly isn't the case in the DALL-E training dataset, because "medical doctor" overwhelmingly yields white dudes-- even after OpenAI's effort at removing bias.
eproxus 4y ago
But it’s also about how you get there. If you only expose kids to pictures of white male doctors you’re going to give them a bias which will shape their lives and by extension the society around them. I think techno libertarian suggestions like these are dangerous because they assume there’s one “canonical” place to fix these issues and all other places can just reflect the status quo, without affecting it (which in my opinion is not possible). It’s like the old saying “dress for the job you want, not the job you have”.
- mlyle 4y ago
  Devil's advocate: Making depictions more diverse than society helps conceal social problems and encourages people to deny them. Social problems are messy and full of situations like this where people can reasonably disagree and have decent, good-faith rationales for both sides, and we lack the kind of evidence that allows us to have strong confidence in our guesses about what would help.

mlyle 4y ago

> There are not enough people in that job that are not white and male. Have you looked at the actual demographics of medical doctors in the US? 54% are women, and 35% are nonwhite. But when we have media depictions of doctors, I agree they tend to be white and male. So, what should DALL-E conform to? Should it conform to A) our actual present society, B) the biased original dataset (which leans both towards the past and towards existing media biases), or C) some idealized version of society? I got 12 white dudes, one Southeast Asian woman, one Southeast Asian looking man, and two men that I'm not sure of their race when I tried this just now (quite possibly white). This is despite OpenAI's efforts to debias it, and isn't representative of current physician demographics. But if AI just represents and reinforces extant biases-- and worse, AI is used to produce art and text that ends up in other AIs training sets -- how do we ever get out of this mess? The people who produce, publish, and productize AI do have some degree of editorial responsibility. > But it turns out there is no "morally neutral". Of course not. Hume pointed out long ago that you can't transform positive statements into normative ones. But all of this is a little offtopic, anyways. This is about when it's reasonable to refuse to return a result. "Hey, your answer had the N-word in it, and we know most of the time our model does that it's offensive-- so we're just not going to return a result, sorry." I think this is a reasonable path to take when you know that your model has some behaviors that are socially questionable.

GameOfFrowns 4y ago
>54% are women, and 35% are nonwhite. But when we have media depictions of doctors, I agree they tend to be white and male What's the issue? I used to watch a lot of medical dramas on TV and in my opinion the black rockstar MDs are way overrepresented in comparison to their real-life numbers: '5.0%' in 2018 in the US[1] in real-life vs. '19.4%'[2] on TV [1]https://www.aamc.org/data-reports/workforce/interactive-data/figure-18-percentage-all-active-physicians-race/ethnicity-2018 https://www.aamc.org/data-reports/workforce/interactive-data... [2]https://www.bluetoad.com/publication/?i=671309&article_id=3748569&view=articleBrowser&ver=html5 https://www.bluetoad.com/publication/?i=671309&article_id=37...
- mlyle 4y ago
  > What's the issue? I used to watch a lot of medical dramas on TV and in my opinion the black rockstar MDs are way overrepresented in comparison to their real-life numbers: Well, this clearly isn't the case in the DALL-E training dataset, because "medical doctor" overwhelmingly yields white dudes-- even after OpenAI's effort at removing bias.

eproxus 4y ago

But it’s also about how you get there. If you only expose kids to pictures of white male doctors you’re going to give them a bias which will shape their lives and by extension the society around them. I think techno libertarian suggestions like these are dangerous because they assume there’s one “canonical” place to fix these issues and all other places can just reflect the status quo, without affecting it (which in my opinion is not possible). It’s like the old saying “dress for the job you want, not the job you have”.

mlyle 4y ago
Devil's advocate: Making depictions more diverse than society helps conceal social problems and encourages people to deny them. Social problems are messy and full of situations like this where people can reasonably disagree and have decent, good-faith rationales for both sides, and we lack the kind of evidence that allows us to have strong confidence in our guesses about what would help.